1. Field of the Invention
The present invention relates to computerized simulation of hydrocarbon reservoirs in the earth, and in particular to simulation and forecasting of production from such reservoirs with determination of fluid motion conditions in cells of the reservoirs.
2. Description of the Related Art
The early development of compositional reservoir simulators in the industry was, so far as is known, restricted to reservoir models small enough to be characterized by a relatively small number of cells (of the order of 100,000) into which the reservoir of interest was organized. Models of this early type provided adequate numerical resolution for small to medium size reservoirs or fields.
The early models became too coarse in data content and accuracy for what have become known as giant oil and gas fields. Giant reservoirs are those mammoth subsurface reservoirs at various locations on the earth containing hydrocarbons and other fluids. In giant reservoirs, there may be thousands of wells, and possibly hundreds of well groups, with tens of thousands of completions, when the total number of wells is considered. For giant reservoirs, the sheer volume of the data involved became a problem in simulation and analysis of performance over a period of time.
In addition, the increased accuracy of detailed seismic-data which samples the reservoir at 25-meter areal (x and y) intervals, has begun to demand models of hundreds of millions to billions of cells to assimilate all the available detail, which in turn has been intended to result in more accurate predictions over the life of the reservoir and lead to higher ultimate oil and gas recovery.
There has also been increased interest in reservoir analysis for taking into account enhanced oil recovery methods and CO2 sequestration. In order that simulation results for this purpose be accurate, inorganic components (such as nitrogen, CO2, sulfides, for example) had to be included along with the hydrocarbons and water as reservoir fluids which would be present in the reservoirs as a result of these processes. Inclusion of inorganic components into the reservoir simulation process thus added to the already large number of reservoir hydrocarbon components and water.
Compositional reservoir simulation has required fast and accurate solution of a linearized system of equations regarding unknown parameters or variables of interest in each of the grid blocks in the reservoir at each Newton iteration of every time step. Given the increasing role of compositional simulation for more accurate fluid description and in enhanced oil recovery methods and CO2 sequestration, the number of unknowns per grid-block has increased from an original 3 for black-oil problems to 10 or more in compositional models. At the same time, a technique known as seismic-scale reservoir simulation with more detailed geological description via integration of seismic data has increased the number of grid blocks into the hundreds of millions to billions.
Iterative linear solution of large systems of equations has become an essential component of oil-and-gas industry reservoir simulations, often accounting for 40% or more of total simulation time. Faster linear solution computations therefore mean quicker turnaround time in reservoir simulation since this linearized system of reservoir equations must be solved several times, about 3 to 7 (once for every Newton iteration in a time-step). Reservoir simulations have required thousands of these time-steps.
The linear solver determines the “correction” required for the Newton iteration to converge to the solution of the underlying non-linear system of equations. Simulation speed is becoming all the more essential as what are known as Intelligent Field operations capture field data in real-time and require a simulation capability that can keep up with online data acquisition rates.
U.S. Pat. No. 7,526,418, of which Applicants are co-inventors, and which is of common ownership to the present invention, is a compositional reservoir simulator which performed simulations in shared memory supercomputers, distributed memory supercomputers or clusters of personal computers (PC's) configured as computer data processing units (CPU's). Other reservoir simulation efforts using CPU's are U.S. Pat. Nos. 7,516,056 and 7,684,967.